Civil, Construction and Environmental Engineering
  

  

  

Publications

Selected Peer-reviewed Journal Papers


---------- 2024 ----------

115. Bozorg-Haddad, O., M. Bahrami, A. Gholami, X. Chu, and H. A. Loaiciga. 2024. Investigation and classification of water resources management strategies: possible threats and solutions. Natural Hazards, 1-26, doi:10.1007/s11069-024-06589-y.

---------- 2023 ----------

114. Khanaum, M. M., T. Qi, K. D. Boutin, M. L. Otte, Z. Lin, and X. Chu. 2023. Assessing the impacts of wetlands on discharge and nutrient loading: Insights from restoring past wetlands with GIS-based analysis and modeling. Wetlands, 43, 103, 1-20, doi:10.1007/s13157-023-01752-w.

113. Qi, T., M. M. Khanaum, K. Boutin, M. L. Otte, Z. Lin, and X. Chu. 2023. Incorporating wetland delineation and impacts in watershed-scale hydrologic modeling. Water, 15, 2518, 1-19, doi:10.3390/w15142518.

112. Tahmasebi Nasab, M. and X. Chu. 2023. Impacts of temperature data sets on macroscale snowmelt simulations in the Missouri River Basin. Journal of Cold Regions Engineering, 37(2), 04023003, 1-13, doi:10.1061/JCRGEI/CRENG-580.

111. Wang, N. and X. Chu. 2023. A modified SCS curve number method for temporally varying rainfall excess simulation. Water, 15, 2374, 1-19, doi:10.3390/w15132374.

110. Bozorg-Haddad, O., M. Delpasand, S. ZamanZad-Ghavidel, X. Chu. 2023. Developing a novel social-water capital index by gene expression programming. Environment, Development and Sustainability. doi:10.1007/s10668-023-03807-8.

109. Rezaee, A., O. Bozorg-Haddad, and X. Chu. 2023. Comparison of data-driven methods in the prediction of hydro-socioeconomic parameters. AQUA - Water Infrastructure, Ecosystems and Society, 72(4), 438-455, doi:10.2166/aqua.2023.161.

108. Jamei, M., M. Ali, M. Karbasi, E. Sharma, M. Jamei, X. Chu, and Z. M. Yaseen. 2023. A high dimensional features-based cascaded forward neural network coupled with MVMD and Boruta-GBDT for multi-step ahead forecasting of surface soil moisture. Engineering Applications of Artificial Intelligence, 120, 105895, 1-25, doi:10.1016/j.engappai.2023.105895.

107. Jamei, M., M. Karbasi, M. Ali, A. Malik, X. Chu, and Z. M. Yaseen. 2023. A novel global solar exposure forecast model based on air temperature: Designing a new multi-processing ensemble deep learning paradigm. Expert Systems with Applications, 222, 119811, 1-22, doi:10.1016/j.eswa.2023.119811.

106. Jamei, M., B. Karimi, M. Ali, F. Alinazari, M. Karbasi, E. Maroufpoor, and X. Chu. 2023. A comprehensive investigation of wetting distribution pattern on sloping lands under drip irrigation: A new gradient boosting multi-filtering-based deep learning approach. Journal of Hydrology, 620, 129402, 1-19, doi:10.1016/j.jhydrol.2023.129402.

105. Karbasi, M. M. Jamei, M. Ali, A. Malik, X. Chu, A. A. Farooque, and Z. M. Yaseen. 2023. Development of an enhanced bidirectional recurrent neural network combined with time-varying filter-based empirical mode decomposition to forecast weekly reference evapotranspiration. Agricultural Water Management, 290, 108604, 1-16, doi:10.1016/j.agwat.2023.108604.

---------- 2022 ----------

104. Bazrkar, M. H. and X. Chu. 2022. Development of category-based scoring support vector regression (CBS-SVR) for drought prediction. Journal of Hydroinformatics, 24(1), 202-222, doi:10.2166/hydro.2022.104.

103. Zeng, L., H. Shen, Y. Cui, X. Chu, and J. Shao. 2022. Incorporating the filling-spilling feature of depressions into hydrologic modeling. Water, 14, 652, 1-16, doi:10.3390/w14040652.

102. Lin, T., Z. Lin, S.H. Lim, X. Jia, and X. Chu. 2022. A spatial agent-based model for hydraulic fracturing water distribution, Frontiers in Environmental Science, 10:1025559, 1-19, doi:10.3389/fenvs.2022.1025559.

101. Li, Y. X. Fu, X. Chu, and S. Liu. 2022. A conflict resolution model for reservoir operation in dry seasons under channel alteration. Journal of Hydrology, 610, 127899, 1-12, doi:10.1016/j.jhydrol.2022.127899.

100. Pandey, M., M. Jamei, I. Ahmadianfar, M. Karbasi, A. S. Lodhi, and X. Chu. 2022. Assessment of scouring around submerged spur dike in cohesive sediment mixtures: A comparative study on three rigorous machine learning models. Journal of Hydrology, 606, 127330, 1-18, doi:10.1016/j.jhydrol.2021.127330.

99. Chen, H., I. Ahmadianfar, G. Liang, H. Bakhsizadeh, B. Azad, and X. Chu. 2022. A successful candidate strategy combined with Runge-Kutta optimization for multi-hydropower reservoir optimization. Expert Systems with Applications, 209, 118383, 1-18, doi:10.1016/j.eswa.2022.118383.

98. Arefinia, A., O. Bozorg-Haddad, K. Ahmadaali, J. Bazrafshan, B. Zolghadr-Asli, and X. Chu. 2022. Estimation of geographical variations in virtual water content and crop yield under climate change: comparison of three data mining approaches. Environment, Development and Sustainability, 24, 8378-8396, doi:10.1007/s10668-021-01788-0.

97. Kazemi, M., O. Bozorg-Haddad, E. Fallah-Mehdipour, and X. Chu. 2022. Optimal water resources allocation in transboundary river basins according to hydropolitical consideration. Environment, Development and Sustainability, 24, 1188-1206, doi:10.1007/s10668-021-01491-0.

96. Bozorg-Haddad, O., P. Yari, M. Delpasand, and X. Chu. 2022. Reservoir operation under influence of the joint uncertainty of inflow and evaporation. Environment, Development and Sustainability, 24, 2914-2940, doi:10.1007/s10668-021-01560-4.

95. Bozorg-Haddad, O., P. Dehghan, B. Zolghadr-Asli, V. P. Singh, Xuefeng Chu, and H. A. Loaiciga. 2022. System dynamics modeling of lake water management under climate change, Scientific Reports, 12, 1-17, 5828, doi:10.1038/s41598-022-09212-x.

94. Yaghoubzadeh-Bavandpour, A., O. Bozorg-Haddad, M. Rajabi, B. Zolghadr-Asli, and X. Chu. 2022. Application of swarm intelligence and evolutionary computation algorithms for optimal reservoir operation. Water Resources Management, 36, 2275-2292, doi:10.1007/s11269-022-03141-0.

93. Karbasi, M., M. Jamei, M. Ali, S. Abdulla, X. Chu, and Z. M. Yaseen. 2022. Developing a novel hybrid Auto Encoder Decoder Bidirectional Gated Recurrent Unit model enhanced with Empirical Wavelet Transform and Boruta-Catboost to forecast Significant Wave Height. Journal of Cleaner Production, 379, 134820, 1-21, doi:10.1016/j.jclepro.2022.134820.

92. Khorsandi, M., P-S. Ashofteh, F. Azadi, and X. Chu. 2022. Multi-objective firefly integration with the K-nearest neighbor to reduce simulation model calls to accelerate the optimal operation of multi-objective reservoirs. Water Resources Management, 36, 3283-3304, doi:10.1007/s11269-022-03201-5.

---------- 2021 ----------

91. Zeng, L. and X. Chu. 2021. Integrating depression storages and their spatial distribution in watershed-scale hydrologic modeling. Advances in Water Resources, 151, 103911, 1-14, doi:10.1016/j.advwatres.2021.103911.

90. Zeng, L. and X. Chu. 2021. A new probability-embodied model for simulating variable contributing areas and hydrologic processes dominated by surface depressions. Journal of Hydrology, 602, 126762, 1-15, doi:10.1016/j.jhydrol.2021.126762.

89. Bazrkar, M. H. and X. Chu. 2021. Ensemble stationary-based support vector regression for drought prediction under changing climate. Journal of Hydrology, 603, 127059, 1-14, doi:10.1016/j.jhydrol.2021.127059.

88. Wang, N., X. Chu, and X. Zhang. 2021. Functionalities of surface depressions in runoff routing and hydrologic connectivity modeling. Journal of Hydrology, 593, 125870, 1-16, doi:10.1016/j.jhydrol.2020.125870.

87. Tahmasebi Nasab, M. and X. Chu. 2021. Do sub-daily temperature fluctuations around the freezing temperature alter macro-scale snowmelt simulations? Journal of Hydrology, 596, 125683, 1-14, doi:10.1016/j.jhydrol.2020.125683.

86. Roy, D., X. Jia, X. Chu, and J. Jacobs. 2021. Hydraulic conductivity measurement for three frozen and unfrozen soils in the Red River of the North Basin. Transactions of the ASABE, 64(3), 761-770, doi:10.13031/trans.14224.

85. Li, J., J. Huang, X. Chu, and J. R. Lund. 2021. An improved peaks-over-threshold method and its application in the time-varying design flood. Water Resources Management, 35, 933-948, doi:10.1007/s11269-020-02758-3.

84. Shabani A, X. Zhang, X. Chu, H. Zheng. 2021. Automatic calibration for CE-QUAL-W2 model using improved global-best harmony search algorithm. Water, 13(16), 2308, 1-15, doi:10.3390/w13162308.

83. Abdi, B., O. Bozorg-Haddad, and X. Chu. 2021. Uncertainty analysis of model inputs in riverine water temperature simulations. Scientific Reports, 11, 1-14, 19908, doi:10.1038/s41598-021-99371-0.

82. Enayati, M., O. Bozorg-Haddad, E. Fallah-Mehdipour, B. Zolghadr-Asli, and X. Chu. 2021. A robust multiple-objective decision-making paradigm based on the water-energy-food security nexus under changing climate uncertainties. Scientific Reports, 11, 1-14, 20927, doi:10.1038/s41598-021-99637-7.

81. Abdi-Dehkordi, M., O. Bozorg-Haddad, and X. Chu. 2021. Development of a combined index to evaluate sustainability of water resources systems. Water Resources Management, 35, 2965-2985, doi:10.1007/s11269-021-02880-w.

80. Rezaee, A., O. Bozorg-Haddad, and X. Chu. 2021. Reallocation of water resources according to social, economic, and environmental parameters. Scientific Reports, 11, 1-13, 17514, doi:10.1038/s41598-021-96680-2.

79. Oliazadeh, A., O. Bozorg-Haddad, M. Mani, and X. Chu. 2021. Developing an urban runoff management model by using satellite precipitation datasets to allocate low impact development systems under climate change conditions. Theoretical and Applied Climatology, 146, 675-687, doi:10.1007/s00704-021-03744-4.

78. Bozorg-Haddad, O., B. Zolghadr-Asli, X. Chu, and H. A. Loaiciga. 2021. Intense extreme hydro-climatic events take a toll on society. Natural Hazards, 108, 2385-2391, doi:10.1007/s11069-021-04749-y.

77. Bozorg-Haddad, O., M. Azad, E. Fallah-Mehdipour, M. Delpasand, and X. Chu. 2021. Verification of FPA and PSO algorithms for rule curve extraction and optimization of single- and multi-reservoir systems' operations considering their specific purposes. Water Supply, 21(1), 166-188, doi:10.2166/ws.2020.274.

76. Fallah-Mehdipour, E., O. Bozorg-Haddad, and X. Chu. 2021. Environmental demand effects on the energy generation of Karkheh reservoir: Base and climate change conditions. Environment, Development and Sustainability, 23, 13165-13181, doi:10.1007/s10668-020-01204-z.

75. Zolghadr-Asli, B., O. Bozorg-Haddad, M. Enayati, and X. Chu. 2021. A review of 20-year applications of multi-attribute decision-making in environmental and water resources planning and management. Environment, Development and Sustainability, 23, 14379-14404, doi:10.1007/s10668-021-01278-3.

74. Naghdia, S., O. Bozorg-Haddad, M. Khorsandi, and X. Chu. 2021. Multi-objective optimization for allocation of surface water and groundwater resources. Science of The Total Environment, 776, 146026, 1-12, doi:10.1016/j.scitotenv.2021.146026.

73. Enayati, M., O. Bozorg-Haddad, J. Bazrafshan, S. Hejabi, and X. Chu. 2021. Bias correction capabilities of quantile mapping methods for rainfall and temperature variables. Journal of Water and Climate Change, 12(2), 401-419, doi:10.2166/wcc.2020.261.

72. Jamei, M., I. Ahmadianfar, X. Chu, and Z. M. Yaseen. 2021. Estimation of triangular side orifice discharge coefficient under a free flow condition using data-driven models. Flow Measurement and Instrumentation, 77, 101878, 1-14, doi:10.1016/j.flowmeasinst.2020.101878.

71. Pandey, M., M. Jamei, M. Karbasic, I. Ahmadianfard, and X. Chu. 2021. Prediction of maximum scour depth near spur dikes in uniform bed sediment using stacked generalization ensemble tree-based frameworks. Journal of Irrigation and Drainage Engineering. 147(11), 04021050, 1-19, doi:10.1061/(ASCE)IR.1943-4774.0001610.

70. Ahmadianfar, I., M. Jamei, and X. Chu. 2021. Prediction of local scour around circular piles under waves using a novel artificial intelligence approach. Marine Georesources & Geotechnology, 39(1), 44-55, doi:10.1080/1064119X2019.1676335.

69. Ahmadianfar, I., A. A. Heidari, A. H. Gandomi, X. Chu, and H. Chen. 2021. RUN beyond the metaphor: An efficient optimization algorithm based on Runge Kutta method. Expert Systems with Applications, 181, 115079, 1-22, doi:10.1016/j.eswa.2021.115079.

68. Azadi, F. P-S. Ashofteh, and X. Chu. 2021. Evaluation of the effects of climate change on thermal stratification of reservoirs. Sustainable Cities and Society, 66, 102531, 1-12, doi:10.1016/j.scs.2020.102531.

---------- 2020 ----------

67. Wang, N. and X. Chu. 2020. Revised Horton model for event and continuous simulations of infiltration, Journal of Hydrology, 589, 125215, 1-11, doi:10.1016/j.jhydrol.2020.125215.

66. Wang, N. and X. Chu. 2020. A new algorithm for delineation of surface depressions and channels. Water, 12(1), 7, 1-14, doi:10.3390/w12010007.

65. Zeng, L. J. Shao, and X. Chu. 2020. Improved hydrologic modeling for depression-dominated areas, Journal of Hydrology, 590, 125269, 1-12, doi:10.1016/j.jhydrol.2020.125269.

64. Bazrkar, M. H. and X. Chu. 2020. New standardized base flow index for identification of hydrologic drought in the Red River of the North Basin. Natural Hazards Review, 21(4), 05020011, 1-8, doi:10.1061/(ASCE)NH.1527-6996.0000414.

63. Bazrkar, M. H., J. Zhang, and X. Chu. 2020. Hydroclimatic aggregate drought index (HADI): A new approach for identification and categorization of drought in cold climate regions. Stochastic Environmental Research and Risk Assessment, 34(11), 1847-1870, doi:10.1007/s00477-020-01870-5.

62. Tahmasebi Nasab, M. and X. Chu. 2020. Macro-HyProS: A new macro-scale hydrologic processes simulator for depression-dominated cold climate regions. Journal of Hydrology, 580, 124366, 1-20, doi:10.1016/j.jhydrol.2019.124366.

61. Grimm, K. and X. Chu. 2020. Depression threshold control proxy to improve HEC-HMS modeling of depression-dominated watersheds, Hydrological Sciences Journal, 65(2), 200-211, doi:10.1080/02626667.2019.1690148.

60. Shabani, A., X. Zhang, X. Chu, T.P. Dodd, and H. Zheng. 2020. Mitigating impact of Devils Lake flooding on the Sheyenne River sulfate concentration. Journal of the American Water Resources Association, 56(2), 297-309, doi:10.1111/1752-1688.12825.

59. Roy, D., X. Jia, D. Steele, X. Chu, and Z. Lin. 2020. Infiltration into frozen silty clay loam soil with different soil water contents in the Red River of the North Basin in the U.S. Water, 12(2), 321, 1-20, doi:10.3390/w12020321.

58. Bozorg-Haddad, O., M. Aboutalebi, X. Chu, and H.A. Loaiciga. 2020. Assessment of potential of intraregional conflicts by developing a transferability index for inter-basin water transfers, and their impacts on the water resources. Environmental Monitoring and Assessment, 192, 40, 1-16, doi:10.1007/s10661-019-8011-1.

57. Bozorg-Haddad, O., B. Zolghadr-Asli, P. Sarzaeim, M. Aboutalebi, X. Chu, and H. A. Loaiciga. 2020. Evaluation of water shortage crisis in the Middle East and possible remedies. Journal of Water Supply: Research and Technology - AQUA, 69(1), 85-98, doi:10.2166/aqua.2019.049.

56. Ahmadianfar, I., M. Jamei, and X. Chu. 2020. A novel hybrid wavelet-locally weighted linear regression (W-LWLR) model for electrical conductivity (EC) prediction in surface water. Journal of Contaminant Hydrology, 232, 103641, 1-17, doi:10.1016/j.jconhyd.2020.103641.

55. Ahmadianfar, I., O. Bozorg-Haddad, and X. Chu. 2020. Gradient-based optimizer: A new metaheuristic optimization algorithm. Information Sciences, 540, 131-159, doi:10.1016/j.ins.2020.06.037.

54. Jamei, M., I. Ahmadianfar, X. Chu, and Z. M. Yaseen. 2020. Prediction of surface water total dissolved solids using hybridized wavelet-multigene genetic programming: New approach. Journal of Hydrology, 589, 125335, 1-15, doi:10.1016/j.jhydrol.2020.125335.

---------- 2019 ----------

53. Chu, X., Z. Lin, M. Tahmasebi Nasab, L. Zeng, K. Grimm, M. H. Bazrkar, N. Wang, X. Liu, X. Zhang, and H. Zheng. 2019. Macro-scale grid-based and subbasin-based hydrologic modeling: joint simulation and cross-calibration. Journal of Hydroinformatics, 21(1), 77-91, doi:10.2166/hydro.2018.026.

52. Wang, N., X. Zhang, and X. Chu. 2019. New model for simulating hydrologic processes under influence of surface depressions. Journal of Hydrologic Engineering, 24(5), 04019008, 1-13, doi:10.1061/(ASCE)HE.1943-5584.0001772.

51. Kadioglu H., H. Hatterman-Valenti, X. Jia, X. Chu, H. Aslan, and H. Simsek. 2019. Groundwater table effects on the yield, growth, and water use of canola (Brassica napus L.) plant. Water. 11(8), 1730, 1-12, doi:10.3390/w11081730.

50. Sun, Z., X. Fu, and X. Chu. 2019. Assessing the impacts of reservoir operation on downstream water diversions using a simplified flow model. Hydrological Sciences Journal, 64(12), 1488-1503, doi:10.1080/02626667.2019.1649410.

49. Xu, Y, X. Fu, and X. Chu. 2019. Analyzing the impacts of climate change on hydro-environmental conflict-resolution management. Water Resources Management, 33(4), 1591-1607, doi:10.1007/s11269-019-2186-7.

48. Golfam, P., P-S. Ashofteh, T. Rajaee, and X. Chu. 2019. Prioritization of water allocation for adaptation to climate change using multi-criteria decision making (MCDM). Water Resources Management, 33, 3401-3416, doi:10.1007/s11269-019-02307-7.

47. Ahmadianfar, I., Z. Khajeh, S.-A. Asghari-Pari, and X. Chu. 2019. Developing optimal policies for reservoir systems using a multi-strategy optimization algorithm, Applied Soft Computing, 80, 888-903, doi:10.1016/j.asoc.2019.04.004.

46. Ashofteh, P-S., T. Rajaee, P. Golfam, and X. Chu. 2019. Applying climate adaptation strategies for improvement of management indexes of a river-reservoir irrigation system. Irrigation and Drainage, 68(3), 420-432, doi:10.1002/ird.2336.

45. Zolghadr-Asli, B., O. Bozorg-Haddad, P. Sarzaem, and X. Chu. 2019. Investigating the variability of GCMs' simulations using time series analysis. Journal of Water and Climate Change, 10(3), 449-463, jwc2018099, doi:10.2166/wcc.2018.099.

44. Zolghadr-Asli, B., O. Bozorg-Haddad, and X. Chu. 2019. Effects of the uncertainties of climate change on the performance of hydropower systems. Journal of Water and Climate Change, 10(3), 591-609, jwc2018120, doi:10.2166/wcc.2018.120.

43. Ahmadianfar, I., O. Bozorg-Haddad, and X. Chu. 2019. Optimizing multiple linear rules for multi-reservoir hydropower systems using an optimization method with an adaptation strategy. Water Resources Management, 33, 4265-4286, doi:10.1007/s11269-019-02364-y.

---------- 2000-2018 ----------

42. Tahmasebi Nasab, M., K. Grimm, M. H. Bazrkar, L. Zeng, A. Shabani, X. Zhang, and X. Chu. 2018. SWAT modeling of non-point source pollution in depression-dominated basins under varying hydroclimatic conditions, International Journal of Environmental Research and Public Health, 15, 2492, 1-17, doi:10.3390/ijerph15112492.

41. Grimm, K and X. Chu. 2018. Modeling of spatiotemporal variations in runoff contribution areas and analysis of hydrologic connectivity. Land Degradation & Development, 29(8), 2629-2643, doi:10.1002/ldr.3076.

40. Grimm, K., M. Tahmasebi Nasab, and X. Chu. 2018. TWI computations and topographic analysis of depression-dominated surfaces. Water, 10, 663, 1-12, doi:10.3390/w10050663.

39. Chu, X., X. Jia, and Y. Liu. 2018. Quantification of Wetting Front Movement under the Influence of Surface Topography. Soil Research, 56(4):382-395, doi:10.1071/SR17071.

38. Abdi-Dehkordi, M., O. Bozorg-Haddad, and X. Chu. 2018. Determination of optimized cropping patterns according to crop yield response under baseline condition and climate-change condition, Irrigation and Drainage, 67(5), 654-669, doi:10.1002/ird.2279.

37. Bahrami, M., O. Bozorg-Haddad, and X. Chu. 2018. Application of cat swarm optimization algorithm for optimal reservoir operation. Journal of Irrigation and Drainage Engineering, 144(1), 04017057, 1-10, doi:10.1061/(ASCE)IR.1943-4774.0001256.

36. Liu, X., N. Wang, J. Shao, and X. Chu. 2017. An automated processing algorithm for flat areas resulting from DEM filling and interpolation. ISPRS International Journal of Geo-Information, 6(11), 376:1-14, doi:10.3390/ijgi6110376.

35. Bozorgi, A., O. Bozorg-Haddad, M.-M. Rajabi, M. Latifi, and X. Chu. 2017. Applications of the anarchic society optimization (ASO) algorithm for optimizing operations of single and continuous multi-reservoir systems. Journal of Water Supply: Research and Technology ¨C AQUA, 66(7), 556-573, doi:10.2166/aqua.2017.137.

34. Tahmasebi Nasab, M., J. Zhang, and X. Chu. 2017. A New Depression-Dominated Delineation (D-cubed) Method for Improved Watershed Modeling. Hydrological Processes. 31(19), 3364-3378, doi:10.1002/hyp.11261.

33. Tahmasebi Nasab, M., V. Singh, and X. Chu. 2017. SWAT modeling for depression-dominated areas: How do depressions manipulate hydrologic modeling? Water. 9(1), 58:1-14, doi: 10.3390/w9010058.

32. Wang, X., X. Chu, T. Liu, X. Cheng, and R. Whittecar. 2017. Water-soil-vegetation dynamic interactions in changing climate. Water, 9(10), 740:1-8, doi:10.3390/w9100740.

31. Chu, X. 2017. Delineation of pothole-dominated wetlands and modeling of their threshold behaviors. Journal of Hydrologic Engineering, 22(1), 1-11, D5015003, doi:10.1061/(ASCE)HE.1943-5584.0001224.

30. Zolghadr-Asli, B., O. Bozorg-Haddad, and X. Chu. 2017. Strategic importance and safety of water resources. Journal of Irrigation and Drainage Engineering, 143(7), 02517001, 1-6, doi:10.1061/(ASCE)IR.1943-4774.0001181.

29. Zolghadr-Asli, B., O. Bozorg-Haddad, and X. Chu. 2017. Brief chronicle of water wars: Search for global peace. Journal of Irrigation and Drainage Engineering, 143(7), 02517002, 1-6, doi:10.1061/(ASCE)IR.1943-4774.0001186.

28. Habtezion, N., M. Tahmasebi Nasab, and X. Chu. 2016. How does DEM resolution affect microtopographic characteristics, hydrologic connectivity, and modelling of hydrologic processes? Hydrological Processes. 30(25), 4870-4892, doi:10.1002/hyp.10967.

27. Singh, V., M. K. Goyal, and X. Chu. 2016. Multicriteria evaluation approach for assessing parametric uncertainty during extreme peak and low flow conditions over snow glaciated and inland catchments. Journal of Hydrologic Engineering, 21(1), 04015044, 1-17, doi: 10.1061/(ASCE)HE.1943-5584.0001217.

26. Yang, J. and X. Chu. 2015. A new modeling approach for simulating microtopography-dominated, discontinuous overland flow on infiltrating surfaces. Advances in Water Resources, 78:80-93, doi:10.1016/j.advwatres.2015.02.004.

25. Chu, X., G. Padmanabhan, and D. Bogart. 2015. Microrelief-controlled overland flow generation: Laboratory and field experiments. Applied and Environmental Soil Science. Volume 2015, Article ID 642952, 11 pages, doi:10.1155/2015/642952.

24. Zhang, J. and X. Chu. 2015. Impact of DEM resolution on puddle characterization: Comparison of different surfaces and methods. Water, 7:2293-2313, doi:10.3390/w7052293.

23. Chu, X., J. Yang, Y. Chi, and J. Zhang. 2013. Dynamic puddle delineation and modeling of puddle-to-puddle filling-spilling-merging-splitting overland flow processes. Water Resources Research. 49(6):3825-3829, doi:10.1002/wrcr.20286.

22. Yang, J. and X. Chu. 2013. Quantification of the spatio-temporal variations in hydrologic connectivity of small-scale topographic surfaces under various rainfall conditions. Journal of Hydrology. 505:65-77, doi:10.1016/j.jhydrol.2013.09.013.

21. Chu, X., J. Nelis, and R. Rediske. 2013. Preliminary study on the effects of surface microtopography on tracer transport in a coupled overland and unsaturated flow system. Journal of Hydrologic Engineering. 18(10):1241-1249, doi:10.1061/(ASCE)HE.1943-5584.0000729.

20. Yang, J. and X. Chu. 2013. Effects of DEM resolution on surface depression properties and hydrologic connectivity. Journal of Hydrologic Engineering. 18(9):1157-1169, doi:10.1061/(ASCE)HE.1943-5584.0000731.

19. Chu, X. 2012. Improved box model for simulating pesticide transport in the vadose zone with dispersive flux through the boundary layer. Journal of Environmental Engineering, ASCE. 138(5):531-541, doi:10.1061/(ASCE)EE.1943-7870.0000509.

18. Chu, X. and R. Rediske. 2012. Modeling metal and sediment transport in a stream-wetland system. Journal of Environmental Engineering, ASCE. 138(2):152-163, doi:10.1061/(ASCE)EE.1943-7870.0000472.

17. Chu, X., J. Yang, and Y. Chi. 2012. Quantification of soil random roughness and surface depression storage: Methods, applicability, and limitations. Transactions of the ASABE. 55(5):1699-1710, doi:10.13031/2013.42361.

16. Sande, L. and X. Chu. 2012. Laboratory experiments on the effect of microtopography on soil-water movement: Spatial variability in wetting front movement. Applied and Environmental Soil Science. Volume 2012, Article ID 679210, 8 pages, doi:10.1155/2012/679210.

15. Chi, Y., J. Yang, D. Bogart, and X. Chu. 2012. Fractal analysis of surface microtopography and its application in understanding hydrologic processes. Transactions of the ASABE. 55(5):1781-1792, doi:10.13031/2013.42370.

14. Sande, L., X. Chu, and T. DeSutter. 2011. A new method for replicating complex microtopographic surfaces in laboratory soil box experiments. Applied Engineering in Agriculture, 27(4):615-620, doi:10.13031/2013.38208.

13. Kim, Y.J., X. Chu, and S. Gajan. 2011. Brief Communication: Flood of the Red River basin in 2009 and effectiveness of rapid mitigation efforts. Natural Hazards Review, 12(1):1-5, doi:10.1061/(ASCE)NH.1527-6996.0000030.

12. Chu, X. 2010. Pesticide occurrence and distribution in the subsurface environment. Earth Science Frontiers. 17(6):31-38.

11. Fu, Xiang, X. Chu, and Guangming Tan. 2010. Sensitivity analysis for an infiltration-runoff model with parameter uncertainty. Journal of Hydrologic Engineering, ASCE. 15(9):671-679, doi:10.1061/(ASCE)HE.1943-5584.0000243.

10. Chu, X. and A. D. Steinman. 2009. Event and continuous hydrologic modeling with HEC-HMS. Journal of Irrigation and Drainage Engineering, ASCE. 135(1):119-124, doi:10.1061/(ASCE)0733-9437(2009)135:1(119).

9. Steinman, A., X. Chu, and M. Ogdahl. 2009. Spatial and temporal variability of internal and external phosphorus loads in an urbanizing watershed. Aquatic Ecology. 43(1):1-18, doi:10.1007/s10452-007-9147-6.

8. Chu, X. and M. A. Marino. 2007. IPTM-CS: A Windows-based integrated pesticide transport model for a canopy-soil system. Environmental Modelling & Software, 22(9):1316-1327, doi:10.1016/j.envsoft.2006.08.006.

7. Steinman, A.D., B. Biddanda, X. Chu, K. Thompson, and R. Rediske. 2007. Environmental analysis of groundwater in Mecosta County, Michigan. Environmental Monitoring and Assessment. 134:177-189, doi:10.1007/s10661-007-9608-3.

6. Chu, X. and M. A. Marino. 2006. Improved compartmental modeling and application to three-phase contaminant transport in unsaturated porous media. Journal of Environmental Engineering, ASCE, 132(2):211-219, doi:10.1061/(ASCE)0733-9372(2006)132:2(211).

5. Steinman, A.D., R. Rediske, R. Denning, L. Nemeth, X. Chu, D. Uzarski, B. Biddanda, and M. Luttenton. 2006. An environmental assessment of an impacted, urbanized watershed: the Mona Lake Watershed, Michigan. Archiv fur Hydrobiologie, 166:117-144, doi:10.1127/0003-9136/2006/0166-0117.

4. Chu, X. and M. A. Marino. 2005. Determination of ponding condition and infiltration into layered soils under unsteady rainfall. Journal of Hydrology, 313(3-4): 195-207, doi:10.1016/j.jhydrol.2005.03.002.

3. Chu, X. and M. A. Marino. 2004. Semidiscrete pesticide transport modeling and application. Journal of Hydrology, 285(1-4):19-40, doi:10.1016/j.jhydrol.2003.07.004.

2. Chu, X., M. A. Marino, Jingli Shao, and Juanming Xu. 2001. Conjunctive water resources supply-demand management model of Baotou City, China. IAHS Publ., 272:159-166.

1. Chu, X., H. Basagaoglu, M. A. Marino, and R. E. Volker. 2000. Aldicarb transport in the subsurface environment: Comparison of models. Journal of Environmental Engineering, ASCE, 126(2):121-129, doi:10.1061/(ASCE)0733-9372(2000)126:2(121).

Journal Editor's Note


3. Chu, X., A. Mishra, and M. M. Hantush. 2024. Scope and direction of the Journal of Hydrologic Engineering: Serving the hydrology community and beyond. Journal of Hydrologic Engineering, 29(1), 01823001, doi:10.1061/JHYEFF.HEENG-6073.

2. Govindaraju, R.S., M. Hantush, and X. Chu. 2020. Introducing the ASCE Journals' Early Career Editorial Board (ECEB). Journal of Hydrologic Engineering. 25(1), 01619001, doi:10.1061/(ASCE)HE.1943-5584.0001894.

1. Govindaraju, R.S., M. Hantush, and X. Chu. 2019. Editor's Note, New policy for transparency of data, models, and code. Journal of Hydrologic Engineering. 24(3), 01618001, doi:10.1061/(ASCE)HE.1943-5584.0001785.

Selected Book Chapters


24. Bozorg-Haddad, O., S. Jafari, and X. Chu. 2022. Overview of Climate Change in Water Resources Management Studies, p1-28. In: Climate Change in Sustainable Water Resources Management, edited by O. Bozorg-Haddad. ISBN 978-981-19-1897-1. Springer Water. Springer, Singapore. doi:10.1007/978-981-19-1898-8_1.

23. Maroufpoor, S., O. Bozorg-Haddad, and X. Chu. 2020. Geostatistics: Principles and Methods, p229-242. Handbook of Probabilistic Models. ISBN: 978-0-12-816514-0. Butterworth-Heinemann, Elsevier Inc.

22. Bozorg-Haddad, O., M. Bahrami, M. Kazemi, B. Abdi, P. Yari, X. Chu, H. A. Loaiciga. 2019. Water Security and Sustainability: Global Threats and Conflicts, p1-6. In: Fundamentals of Water, Chemistry, Particles, and Ecology, Overview, Encyclopedia of Water: Science, Technology, and Society. ISBN: 9781119300755. John Wiley & Sons, Inc., New York. doi: 10.1002/9781119300762.wsts0090.

21. Zolghadr-Asli, B., O. Bozorg-Haddad, X. Chu. 2019. Hot Hand Fallacy: A Contagious Misinterpretation in Water Resources Sectors, p1-5. In: Human Dimensions, Climate Change and Sustainability, Encyclopedia of Water: Science, Technology, and Society. ISBN: 9781119300755. John Wiley & Sons, Inc., New York. doi: 10.1002/9781119300762.wsts0088.

20. Zolghadr-Asli, B., O. Bozorg-Haddad, X. Chu. 2019. Hydropower in Climate Change, p1-5. In: Human Dimensions, Climate Change and Sustainability, Encyclopedia of Water: Science, Technology, and Society. ISBN: 9781119300755. John Wiley & Sons, Inc., New York. doi: 10.1002/9781119300762.wsts0089.

19. Chu, X. 2018. Quantifying Discontinuity, Connectivity, Variability, and Hierarchy in Overland Flow Generation: Comparison of Different Modeling Methods, p587-603. In: Watershed Runoff and Floods, Hydrologic Modeling, Water Science and Technology Library, vol 81, edited by V. P. Singh, S. Yadav, R. N. Yadava. ISBN: 978-981-10-5800-4. Springer, Singapore. doi: 10.1007/978-981-10-5801-1_41.

18. Zolghadr-Asli, B., O. Bozorg-Haddad, and X. Chu. 2018. Introduction. p1-8. In: Advanced Optimization by Nature-Inspired Algorithms. Studies in Computational Intelligence, vol 720. ISBN: 978-981-10-5220-0. Springer, Singapore. doi: 10.1007/978-981-10-5221-7_1.

17. Bahrami, M., O. Bozorg-Haddad, and X. Chu. 2018. Cat Swarm Optimization (CSO) Algorithm. p9-18. In: Advanced Optimization by Nature-Inspired Algorithms. Studies in Computational Intelligence, vol 720. ISBN: 978-981-10-5220-0. Springer, Singapore. doi: 10.1007/978-981-10-5221-7_2.

16. Rezaei, H., O. Bozorg-Haddad, and X. Chu. 2018. League Championship Algorithm (LCA). p19-30. In: Advanced Optimization by Nature-Inspired Algorithms. Studies in Computational Intelligence, vol 720. ISBN: 978-981-10-5220-0. Springer, Singapore. doi: 10.1007/978-981-10-5221-7_3.

15. Bozorgi, A., O. Bozorg-Haddad, and X. Chu. 2018. Anarchic Society Optimization (ASO) Algorithm. p31-38. In: Advanced Optimization by Nature-Inspired Algorithms. Studies in Computational Intelligence, vol 720. ISBN: 978-981-10-5220-0. Springer, Singapore. doi: 10.1007/978-981-10-5221-7_4.

14. Jafari, S., O. Bozorg-Haddad, and X. Chu. 2018. Cuckoo Optimization Algorithm (COA). p39-49. In: Advanced Optimization by Nature-Inspired Algorithms. Studies in Computational Intelligence, vol 720. ISBN: 978-981-10-5220-0. Springer, Singapore. doi: 10.1007/978-981-10-5221-7_5.

13. Sarzaeim, P., O. Bozorg-Haddad, and X. Chu. 2018. Teaching-Learning-Based Optimization (TLBO) Algorithm. p51-58. In: Advanced Optimization by Nature-Inspired Algorithms. Studies in Computational Intelligence, vol 720. ISBN: 978-981-10-5220-0. Springer, Singapore. doi: 10.1007/978-981-10-5221-7_6.

12. Azad, M., O. Bozorg-Haddad, and X. Chu. 2018. Flower pollination Algorithm (FPA). p59-67. In: Advanced Optimization by Nature-Inspired Algorithms. Studies in Computational Intelligence, vol 720. ISBN: 978-981-10-5220-0. Springer, Singapore. doi: 10.1007/978-981-10-5221-7_7.

11. Zolghadr-Asli, B., O. Bozorg-Haddad, and X. Chu. 2018. Krill Herd Algorithm (KHA). p69-79. In: Advanced Optimization by Nature-Inspired Algorithms. Studies in Computational Intelligence, vol 720. ISBN: 978-981-10-5220-0. Springer, Singapore. doi: 10.1007/978-981-10-5221-7_8.

10. Rezaei, H., O. Bozorg-Haddad, and X. Chu. 2018. Grey Wolf Optimization (GWO) Algorithm. p81-91. In: Advanced Optimization by Nature-Inspired Algorithms. Studies in Computational Intelligence, vol 720. ISBN: 978-981-10-5220-0. Springer, Singapore. doi: 10.1007/978-981-10-5221-7_9.

9. Mohammad-Azari, S., O. Bozorg-Haddad, and X. Chu. 2018. Shark Smell Optimization (SSO) Algorithm. p93-103. In: Advanced Optimization by Nature-Inspired Algorithms. Studies in Computational Intelligence, vol 720. ISBN: 978-981-10-5220-0. Springer, Singapore. doi: 10.1007/978-981-10-5221-7_10.

8. Mani, M., O. Bozorg-Haddad, and X. Chu. 2018. Ant Lion Optimizer (ALO) Algorithm. p105-116. In: Advanced Optimization by Nature-Inspired Algorithms. Studies in Computational Intelligence, vol 720. ISBN: 978-981-10-5220-0. Springer, Singapore. doi: 10.1007/978-981-10-5221-7_11.

7. Abdi-Dehkordi, M., O. Bozorg-Haddad, and X. Chu. 2018. Gradient Evolution (GE) Algorithm. p117-130. In: Advanced Optimization by Nature-Inspired Algorithms. Studies in Computational Intelligence, vol 720. ISBN: 978-981-10-5220-0. Springer, Singapore. doi: 10.1007/978-981-10-5221-7_12.

6. Bahrami, M., O. Bozorg-Haddad, and X. Chu. 2018. Moth-Flame Optimization (MFO) Algorithm. p131-141. In: Advanced Optimization by Nature-Inspired Algorithms. Studies in Computational Intelligence, vol 720. ISBN: 978-981-10-5220-0. Springer, Singapore. doi: 10.1007/978-981-10-5221-7_13.

5. Zolghadr-Asli, B., O. Bozorg-Haddad, and X. Chu. 2018. Crow Search Algorithm (CSA). p143-149. In: Advanced Optimization by Nature-Inspired Algorithms. Studies in Computational Intelligence, vol 720. ISBN: 978-981-10-5220-0. Springer, Singapore. doi: 10.1007/978-981-10-5221-7_14.

4. Zolghadr-Asli, B., O. Bozorg-Haddad, and X. Chu. 2018. Dragonfly Algorithm (DA). p151-159. In: Advanced Optimization by Nature-Inspired Algorithms. Studies in Computational Intelligence, vol 720. ISBN: 978-981-10-5220-0. Springer, Singapore. doi: 10.1007/978-981-10-5221-7_15.

3. Novak, J.M., A.A. Szogi, K.C. Stone, X. Chu, D.W. Watts and M.H. Johnson. 2012. Transport of Nitrate and Ammonium during Tropical Storm and Hurricane induced Stream Flow Events from a Southeastern USA Coastal Plain In-stream Wetland - 1997 to 1999, Chapter 7, p139-158. In: Advances in Hurricane Research - Modelling, Meteorology, Preparedness and Impacts (ISBN 978-953-51-0867-2), edited by K. Hickey. InTech - Open Access Publisher.

2. Chu, X. 2011. Characterization of Microtopography and its Hydrologic Significance, Chapter 1, p1-14. In: Modeling Hydrologic Effects of Microtopographic Features (ISBN 978-1-61668-628-4), edited by X. Wang. Nova Science Publishers, Inc.

1. Chu, X. 2005. Pesticide Occurrence and Distribution in Relation to Use, p655-657. In: Water Encyclopedia: Surface and Agricultural Water, Vol. 3, edited by J.H. Lehr and J. Keeley. John Wiley & Sons, Inc., New York.

Selected Proceeding Papers


14. Tahmasebi Nasab, M. and X. Chu. 2018. Topo-statistical analyses of ponding area versus ponding storage of depression-dominated regions for macro-scale hydrologic modeling, p415-424. In: Watershed Management, Irrigation and Drainage, and Water Resources Planning and Management, Proceedings of the 2018 ASCE World Environmental and Water Resources Congress, edited by Sri Kamojjala, American Society of Civil Engineers, doi: 10.1061/9780784481400.

13. Tahmasebi Nasab, M., K. Grimm, N. Wang, and X. Chu. 2017. Scale Analysis for Depression-Dominated Areas: How Does Threshold Resolution Represent a Surface? P164-174. In: Proceedings of the 2017 ASCE World Environmental and Water Resources Congress, Watershed Management, Irrigation and Drainage, and Water Resources Planning and Management, edited by Christopher N. Dunn and Brain Van Weele, American Society of Civil Engineers. doi: 10.1061/9780784480601.

12. Tahmasebi Nasab, M., X. Jia, and X. Chu. 2016. Modeling of subsurface drainage under varying microtopographic, soil and rainfall conditions, Paper Number 162499952, p133-138. 10th International Drainage Symposium, ASABE, Minneapolis, Minnesota, September 7-9, 2016. doi: 10.13031/ids.202499952.

11. Roy, D., X. Jia, D. Steele, and X. Chu. 2015. Measurement and simulation of infiltration rates into undrained and subsurface drained soils, Paper Number 152190011, p1-9. 2015 ASABE Annual International Meeting, New Orleans, Louisiana, July 26-29, 2015.

10. Chu, X. and N. Habtezion. 2014. Applications of the Green-Ampt Method across Scales, p282-291. In: Water without Borders, Proceedings of the 2014 ASCE World Environmental and Water Resources Congress, edited by Wayne C. Huber. American Society of Civil Engineers.

9. Liu, Y., J. Yang, and X. Chu. 2013. Infiltration and unsaturated flow under the influence of surface microtopography - model simulations and experimental observations, p468-475. In: Showcasing the Future, Proceedings of the 2013 ASCE World Environmental and Water Resources Congress, edited by C. L. Patterson, S. D. Struck, and D. J. Murray. American Society of Civil Engineers.

8. Yang, J. and X. Chu. 2012. Effects of Surface Microtopography on Hydrologic Connectivity. p339-348. In: Crossing Boundaries, Proceedings of the 2012 ASCE World Environmental and Water Resources Congress, Edited by E. D. Loucks. American Society of Civil Engineers.

7. Chu, X., J. Zhang, Y. Chi, and J. Yang. 2010. An improved method for watershed delineation and computation of surface depression storage, p1113-1122. In: Watershed Management 2010: Innovations in Watershed Management Under Land Use and Climate Change, Proceedings of the 2010 Watershed Management Conference, edited by K. W. Potter and D. K. Frevert. American Society of Civil Engineers.

6. Chu, X., J. Zhang, J. Yang, and Y. Chi. 2010. Quantitative evaluation of the relationship between grid spacing of DEMs and surface depression storage, p4447-4457. In: Challenges of Change, Proceedings of the 2010 World Environmental and Water Resources Congress, edited by R. N. Palmer. American Society of Civil Engineers.

5. Chi, Y., J. Yang, and X. Chu. 2010. Characterization of surface roughness and computation of depression storage, p4437-4446. In: Challenges of Change, Proceedings of the 2010 World Environmental and Water Resources Congress, edited by R. N. Palmer. American Society of Civil Engineers.

4. Yang, J., X. Chu, Y. Chi, and L. Sande. 2010. Effects of rough surface slopes on surface depression storage, p4427-4436. In: Challenges of Change, Proceedings of the 2010 World Environmental and Water Resources Congress, edited by R. N. Palmer. American Society of Civil Engineers.

3. Chu, X. and A. D. Steinman. 2008. Continuous hydrologic modeling improved by intensive event data, p1-11. In: Proceedings of the World Environmental and Water Resources Congress 2008 Ahupua'a, edited by R. W. Bakcock, Jr. and R. Walton. American Society of Civil Engineers.

2. Chu, X. and M. A. Marino. 2007. Space and time issues in comparison and evaluation of different pesticide transport models in the vadose zone, p1-9. In: Restoring Our Natural Habitat, Proceedings of the 2007 World Environmental and Water Resources Congress, edited by Karen C. Kabbes. American Society of Civil Engineers.

1. Chu, X. and M. A. Marino. 2006. Simulation of infiltration and surface runoff - A Windows-based hydrologic modeling system HYDROL-INF, p1-8. In: Examining the Confluence of Environmental and Water Concerns, Proceedings of the 2006 World Environmental and Water Resources Congress, edited by Randall Graham. American Society of Civil Engineers.

Software Manuals


6. Chu, X. 2014. HYDROL-INF Modeling System - Hydrologic Research and Teaching Software, Version 6.10, User's Manual, North Dakota State University, 80 pages.

5. Chu, X., J. Zhang, J. Yang, N. Habtezion, Y. Chi, and Y. Yang. 2013. P2P Modeling System, User's Manual, Version 1.50, North Dakota State University, 45 pages.

4. Chu, X., J. Zhang, J. Yang, N. Habtezion, Y. Chi, and Y. Yang. 2013. P2P Tools, User's Manuals, Version 1.50, North Dakota State University, 64 pages.

3. Chu, X., J. Zhang, J. Yang, N. Habtezion, Y. Chi, and Y. Yang. 2013. P2P Education, User's Manual, Version 1.50, North Dakota State University, 10 pages.

2. Chu, X. 2014. IPTM-CS: Integrated Pesticide Transport Model for a Coupled Canopy-Soil System, Version 2.00, User's Manual, North Dakota State University, 139 pages.

1. Chu, X. 2014. IPTM-S: Integrated Pesticide Transport Model for Soils, Version 2.00, User's Manual, North Dakota State University, 130 pages.

Selected Conference Abstracts


13. Chu, X., J. Zhang, and M. Tahmasebi Nasab. 2015. DEM-based Watershed Delineation ¨C Comparison of Different Methods and applications. AGU 2015 Fall Meeting, San Francisco, CA.

12. Chu, X., J. Yang, and N. Habtezion. 2012. Dynamic puddle delineation and threshold-driven hydrotopographic processes. AGU 2012 Fall Meeting, San Francisco, CA.

11. Yang, J., D. Bogart, and X. Chu. 2012. Quantification of the spatio-temporal variability in threshold-controlled overland flow generation processes - A combined experimental and modeling study. AGU 2012 Fall Meeting, San Francisco, CA.

10. Chu, X. 2011. State-of-the-art Hydrology Education: Development of Windows-based and Web-based Interactive Teaching-Learning Software. AGU 2011 Fall Meeting, San Francisco, CA.

9. Chu, X., J. Yang, Y. Chi, Y. Yang, and J. Zhang. 2011. Development of a Windows-based Modeling System for Simulating Microtopography-Controlled Overland Flow. AGU 2011 Fall Meeting, San Francisco, CA.

8. Yang, J. and X. Chu. 2011. Surface Microtopography and Hydrologic Connectivity Analysis. AGU 2011 Fall Meeting, San Francisco, CA.

7. Chu, X., Jessica Higgins, and Jianli Zhang. 2008. Multi-scale DEM-based delineation and quantification of overland flow processes. AGU 2008 Fall Meeting, San Francisco.

6. Novak, J., A. Szogi, X. Chu, and K. Stone. 2008. Extreme storm events causes distinctive nitrogen loads transported through a southeastern USA coastal plain in-stream wetland. Symposium - Restored and Created Wetland Functions under Extreme Climate Events, 2008 Joint Annual Meeting (SSSA-ASA-CSSA), Huston, TX.

5. Chu, X. and M. A. Marino. 2007. Occurrence and Distribution of Agricultural Pesticides and Transport Modeling in Surface and Subsurface Environments. AGU 2007 Fall Meeting, San Francisco.

4. Chu, X. and M. A. Marino. 2005. Development of a Windows-Based Integrated Pesticide Transport Modeling System for a Coupled Canopy and Soil System (IPTM-CS). Cleve Steward, Editor, Extended Abstract Proceedings, AWRA 2005 Annul Water Resources Conference, Seattle, WA.

3. Chu, X., A.D. Steinman, R.R. Rediske, K.M. Thompson, R.L. Denning, L.C. Nemeth. 2003. Watershed Hydrologic Modeling and Application in the Little Black Creek Basin. Lake Michigan: State of the Lake '03, Muskegon, Michigan.

2. Chu, X. and M. A. Marino. 2001. Models for pesticide exposure assessment in surface-subsurface environments. In Water Quality Monitoring and Modeling, edited by John J. Warwick. American Water Resources Association, Middleburg, Virginia.

1. Chu, X., M. A. Marino, Jingli Shao, and Craig Nordmark. 2000. Pesticide transport modeling and application to the Wadsworth Canal Basin, California. In The AGU 2000 Fall Meeting Abstract Volume, published as a supplement to Eos, Transactions, American Geophysical Union (ISSN 0096-3941), Vol. 81, No. 48, Washington DC.